Databricks Certified Data Engineer Associate Exam
Last Update Feb 18, 2026
Total Questions : 159
To help you prepare for the Databricks-Certified-Data-Engineer-Associate Databricks exam, we are offering free Databricks-Certified-Data-Engineer-Associate Databricks exam questions. All you need to do is sign up, provide your details, and prepare with the free Databricks-Certified-Data-Engineer-Associate practice questions. Once you have done that, you will have access to the entire pool of Databricks Certified Data Engineer Associate Exam Databricks-Certified-Data-Engineer-Associate test questions which will help you better prepare for the exam. Additionally, you can also find a range of Databricks Certified Data Engineer Associate Exam resources online to help you better understand the topics covered on the exam, such as Databricks Certified Data Engineer Associate Exam Databricks-Certified-Data-Engineer-Associate video tutorials, blogs, study guides, and more. Additionally, you can also practice with realistic Databricks Databricks-Certified-Data-Engineer-Associate exam simulations and get feedback on your progress. Finally, you can also share your progress with friends and family and get encouragement and support from them.
A Databricks workflow fails at the last stage due to an error in a notebook. This workflow runs daily. The data engineer fixes the mistake and wants to rerun the pipeline. This workflow is very costly and time-intensive to run.
Which action should the data engineer do in order to minimise downtime and cost?
A data engineer wants to create a relational object by pulling data from two tables. The relational object does not need to be used by other data engineers in other sessions. In order to save on storage costs, the data engineer wants to avoid copying and storing physical data.
Which of the following relational objects should the data engineer create?
A data engineer needs to process SQL queries on a large dataset with fluctuating workloads. The workload requires automatic scaling based on the volume of queries, without the need to manage or provision infrastructure. The solution should be cost-efficient and charge only for the compute resources used during query execution.
Which compute option should the data engineer use?